Decoupled Sampling for Real-Time Graphics Pipelines
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MIT-CSAIL-TR-2010-015.pdf
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26.13 MB
Format
Adobe PDF
Checksum (MD5)
6c01431755a866265cde0246d50f9f6a
Author(s)
Ragan-Kelley, Jonathan
Doggett, Michael
Lehtinen, Jaakko
Chen, Jiawen
Durand, Fredo
Advisor(s)
Fredo Durand
Date Issued
March 29, 2010
Citation
RAGAN-KELLEY, J., LEHTINEN, J., CHEN, J., DOGGETT, M., and DURAND, F. 2010. Decoupled Sampling for Real-Time Graphics Pipelines. MIT Computer Science and Artificial Intelligence Laboratory Technical Report Series, MIT-CSAIL-TR-2010-015.
Series/Report no.
MIT-CSAIL-TR-2010-015
Abstract
We propose decoupled sampling, an approach that decouples shading from visibility sampling in order to enable motion blur and depth-of-field at reduced cost. More generally, it enables extensions of modern real-time graphics pipelines that provide controllable shading rates to trade off quality for performance. It can be thought of as a generalization of GPU-style multisample antialiasing (MSAA) to support unpredictable shading rates, with arbitrary mappings from visibility to shading samples as introduced by motion blur, depth-of-field, and adaptive shading. It is inspired by the Reyes architecture in offline rendering, but targets real-time pipelines by driving shading from visibility samples as in GPUs, and removes the need for micropolygon dicing or rasterization. Decoupled Sampling works by defining a many-to-one hash from visibility to shading samples, and using a buffer to memoize shading samples and exploit reuse across visibility samples. We present extensions of two modern GPU pipelines to support decoupled sampling: a GPU-style sort-last fragment architecture, and a Larrabee-style sort-middle pipeline. We study the architectural implications and derive end-to-end performance estimates on real applications through an instrumented functional simulator. We demonstrate high-quality motion blur and depth-of-field, as well as variable and adaptive shading rates.
Subjects
Computer Graphics
Graphics Systems
Graphics Hardware
Terms of Use
Creative Commons Attribution-Share Alike 3.0 Unported
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